Project Abstract Source data verification (SDV) is one of the most expensive, labor-intensive, and error-ridden steps in monitoring clinical trials. During the SDV process, human monitors manually compare information in two or more databases for completeness, consistency, and adherence to the trial protocol. Because SDV is performed manually, it incurs high labor costs and is prone to human-borne errors. Our overall objective with this Phase 1 SBIR grant is to develop a prototype software application that can automate the SDV process. This tool would also incorporate a rules-based engine to compare information in the database to study-specific protocol parameters. Our specific aims are as follows: (1) develop exogenous source data interfaces, (2) develop exogenous configuration data interfaces, (3) design and implement an efficient comparison engine capable of detecting protocol rule violations in the records extracted from multiple exogenous data sources, and (4) perform ?ad hoc ?Study Simulations and Measure the effectiveness of the Swift SDV system.